An observational study of postoperative handoff standardization failures

Application of Within-Methods Triangulation to Analyze Hospital System Health

Qualitative descriptive research can be used when researchers are seeking to find the "how," "what," or "when" of phenomena. The most common qualitative descriptive analysis methods are content and thematic analyses. Data triangulation through content analysis and natural language processing was first described in 2018 for the analysis of nurse-to-nurse communication in an acute care setting. The purpose of this article is to discuss a within-methods data triangulation of interviews done with nurses and nursing leaders in Magnet- and non-Magnet-designated hospitals through integration and application of content analysis, code quantification via the Goodwin statistic, and natural language processing.

Application of a Human Factors and Systems Engineering Approach to Explore Care Transitions of Sepsis Survivors From Hospital to Home Health Care

STUDY AIM

This study aims to describe the transition-in-care work process for sepsis survivors going from hospitals to home health care (HHC) and identify facilitators and barriers to enable practice change and safe care transitions using a human factors and systems engineering approach.

BACKGROUND

Despite high readmission risk for sepsis survivors, the transition-in-care work process from hospitals to HHC has not been described.

METHODS

We analyzed semi-structured needs assessment interviews with 24 stakeholders involved in transitioning sepsis survivors from two hospitals and one affiliated HHC agency participating in the parent implementation science study, I-TRANSFER. The qualitative data analysis was guided by the Systems Engineering Initiative for Patient Safety (SEIPS) framework to describe the work process and identify work system elements.

RESULTS

We identified 31 tasks characterized as decision making, patient education, communication, information, documentation, and scheduling tasks. Technological and organizational facilitators lacked in HHC compared to the hospitals. Person and organization elements in HHC had the most barriers but few facilitators. Additionally, we identified specific task barriers that could hinder sepsis information transfer from hospitals to HHC.

CONCLUSION

This study explored the complex transition-in-care work processes for sepsis survivors going from hospitals to HHC. We identified barriers, facilitators, and critical areas for improvement to enable implementation and ensure safe care transitions. A key finding was the sepsis information transfer deficit, highlighting a critical issue for future study.

APPLICATION

We recommend using the SEIPS framework to explore complex healthcare work processes before the implementation of evidence-based interventions.

Handoffs and the challenges to implementing teamwork training in the perioperative environment

Perioperative handoffs are high-risk events for miscommunications and poor care coordination, which cause patient harm. Extensive research and several interventions have sought to overcome the challenges to perioperative handoff quality and safety, but few efforts have focused on teamwork training. Evidence shows that team training decreases surgical morbidity and mortality, and there remains a significant opportunity to implement teamwork training in the perioperative environment. Current perioperative handoff interventions face significant difficulty with adherence which raises concerns about the sustainability of their impact. In this perspective article, we explain why teamwork is critical to safe and reliable perioperative handoffs and discuss implementation challenges to the five core components of teamwork training programs in the perioperative environment. We outline evidence-based best practices imperative for training success and acknowledge the obstacles to implementing those best practices. Explicitly identifying and discussing these obstacles is critical to designing and implementing teamwork training programs fit for the perioperative environment. Teamwork training will equip providers with the foundational teamwork competencies needed to effectively participate in handoffs and utilize handoff interventions. This will improve team effectiveness, adherence to current perioperative handoff interventions, and ultimately, patient safety.

Improving Handoffs in the Perioperative Environment: A Conceptual Framework of Key Theories, System Factors, Methods, and Core Interventions to Ensure Success

BACKGROUND

Patient handoffs involve the transition of information and responsibility for care from one health care provider to another. They occur frequently during a patient's perioperative care continuum, potentially introducing communication errors that could result in harmful, even fatal consequences. The perioperative environment poses distinct challenges to team communication and patient safety, which in turn leaves the surgical patient uniquely vulnerable to adverse events.

CONCEPTUAL FRAMEWORK

The best way to achieve safe, coordinated handoffs throughout the perioperative continuum has yet to be established. However, a variety of theoretical principles, methods, and interventions have been used successfully in operative and nonoperative contexts among multiple disciplines. Informed by a literature review, the authors describe a conceptual framework for the development, implementation, and sustainment of a multimodal perioperative handoff improvement bundle. The conceptual framework presented here begins with overarching objectives for patient-centered handoff improvement efforts. The article outlines theoretical principles that could be used to guide and inform future multimodal interventions, as well as health care system factors to consider. Further, the authors propose employing data-driven quality improvement and research methodologies to conduct, measure, achieve, and sustain long-term success. Finally, this report describes essential evidence-based interventional components to employ.

IMPLICATIONS

Future efforts to improve handoff safety in the perioperative environment will require a comprehensive evidence-based approach. The authors believe the conceptual framework presented here outlines essential components for success. It integrates proven theoretical frameworks, consideration of system factors, data-driven iterative methods, and synergistic patient-centered interventions.

An evidence synthesis on perioperative Handoffs: A call for balanced sociotechnical solutions

SIGNIFICANCE

Perioperative handoffs interconnect the preoperative, intraoperative, and postoperative phases underlying surgical care to maintain care continuity -yet are prone to coordination and communication failures.

OBJECTIVE

To synthesize evidence on factors affecting the safety and quality of perioperative handoff conduct and process.

MATERIALS AND METHODS

A search of PubMed, EMBASE, and CINAHL was conducted to include observational, descriptive studies of preoperative, intraoperative, and postoperative handoffs published in English language, peer-reviewed journals. Data analysis was informed by the Systems Engineering Initiative for Patient Safety (SEIPS) framework describing the relationship between the work-system, work processes, and outcomes. Study quality was assessed using the Quality Scoring System.

RESULTS

Twenty-three studies were included. Eighteen studies focused on postoperative handoffs, with one on preoperative, three on intraoperative and only one that looked at preoperative/postoperative handoffs combined. The SEIPS framework elucidated the complex inter-related factors (enablers and barriers) related to perioperative handoff safety. While some studies found that the use of standardized handoff tools and protocols and interdisciplinary teamwork were frequently-reported enablers, other studies identified the lack of structured handoff tools and protocols, poor teamwork and communication, and improper use of documentation tools were top-cited barriers affecting handoff quality. Suggestions to ensure handoff safety and quality included implementing structured handoff checklists and protocols and building interprofessional teamwork competencies for effective communication.

DISCUSSION AND CONCLUSION

Our review highlights an urgency to develop more holistic sociotechnical solutions that can create and sustain a balance between technical innovations in tools and technologies and the non-technical interventions/training needed to improve interpersonal relations and teamwork competencies - taken together, can improve the quality and safety of perioperative handoff practice.

Integrating machine learning predictions for perioperative risk management: Towards an empirical design of a flexible-standardized risk assessment tool

BACKGROUND

Surgical patients are complex, vulnerable, and prone to postoperative complications that can potentially be mitigated with quality perioperative risk assessment and management. Several institutions have incorporated machine learning (ML) into their patient care to improve awareness and support clinician decision-making along the perioperative spectrum. Recent research suggests that ML risk prediction can support perioperative patient risk monitoring and management across several situations, including the operating room (OR) to intensive care unit (ICU) handoffs.

OBJECTIVES

Our study objectives were threefold: (1) evaluate whether ML-generated postoperative predictions are concordant with clinician-generated risk rankings for acute kidney injury, delirium, pneumonia, deep vein thrombosis, and pulmonary embolism, and establish their associated risk factors; (2) ascertain clinician end-user suggestions to improve adoption of ML-generated risks and their integration into the perioperative workflow; and (3) develop a user-friendly visualization format for a tool to display ML-generated risks and risk factors to support postoperative care planning, for example, within the context of OR-ICU handoffs.

METHODS

Graphical user interfaces for postoperative risk prediction models were assessed for end-user usability through cognitive walkthroughs and interviews with anesthesiologists, surgeons, certified registered nurse anesthetists, registered nurses, and critical care physicians. Thematic analysis relying on an explanation design framework was used to identify feedback and suggestions for improvement.

RESULTS

17 clinicians participated in the evaluation. ML estimates of complication risks aligned with clinicians' independent rankings, and related displays were perceived as valuable for decision-making and care planning for postoperative care. During OR-ICU handoffs, the tool could speed up report preparation and remind clinicians to address patient-specific complications, thus providing more tailored care information. Suggestions for improvement centered on electronic tool delivery; methods to build trust in ML models; modifiable risks and risk mitigation strategies; and additional patient information based on individual preferences (e.g., surgical procedure).

CONCLUSIONS

ML estimates of postoperative complication risks can provide anticipatory guidance, potentially increasing the efficiency of care planning. We have offered an ML visualization framework for designing future ML-augmented tools and anticipate the development of tools that recommend specific actions to the user based on ML model output.

Exploring patient perspectives on telemedicine monitoring within the operating room

BACKGROUND

Clinical decision support systems and telemedicine for remote monitoring can together support clinicians' intraoperative decision-making and management of surgical patients' care. However, there has been limited investigation on patient perspectives about advanced health information technology use in intraoperative settings, especially an electronic OR (eOR) for remote monitoring and management of surgical patients.

PURPOSE

Our study objectives were: (1) to identify participant-rated items contributing to patient attitudes, beliefs, and level of comfort with eOR monitoring; and (2) to highlight barriers and facilitators to eOR use.

METHODS

We surveyed 324 individuals representing surgical patients across the United States using Amazon Mechanical Turk, an online platform supporting internet-based work. The structured survey questions examined the level of agreement and comfort with eOR for remote patient monitoring. We calculated descriptive statistics for demographic variables and performed a Wilcoxon matched-pairs signed-rank test to assess whether participants were more comfortable with familiar clinicians from local hospitals or health systems monitoring their health and safety status during surgery than clinicians from hospitals or health systems in other regions or countries. We also analyzed open-ended survey responses using a thematic approach informed by an eight-dimensional socio-technical model.

RESULTS

Participants' average age was 34.07 (SD = 10.11). Most were white (80.9%), male (57.1%), and had a high school degree or more (88.3%). Participants reported a higher level of comfort with clinicians they knew monitoring their health and safety than clinicians they did not know, even within the same healthcare system (z = -4.012, p < .001). They reported significantly higher comfort levels with clinicians within the same hospital or health system in the United States than those in a different country (z = -10.230, p < .001). Facilitators and barriers to eOR remote monitoring were prevalent across four socio-technical dimensions: 1) organizational policies, procedures, environment, and culture; 2) people; 3) workflow and communication; and 4) hardware and software. Facilitators to eOR use included perceptions of improved patient safety through a safeguard system and perceptions of streamlined care. Barriers included fears of incorrect eOR patient assessments, decision-making conflicts between care teams, and technological malfunctions.

CONCLUSIONS

Participants expressed significant support for intraoperative telemedicine use and greater comfort with local telemedicine systems instead of long-distance telemedicine systems. Reservations centered on organizational policies, procedures, environment, culture; people; workflow and communication; and hardware and software. To improve the buy-in and acceptability of remote monitoring by an eOR team, we offer a few evidence-based guidelines applicable to telemedicine use within the context of OR workflow. Guidelines include backup plans for technical challenges, rigid care, and privacy standards, and patient education to increase understanding of telemedicine's potential to improve patient care.